1 code implementation • ACL 2022 • Zhe Li, Luoyi Fu, Xinbing Wang, Haisong Zhang, Chenghu Zhou
However, most existing works either ignore the semantic information of relations or predict subjects and objects sequentially.
no code implementations • CCL 2020 • Xiuhong Li, Zhe Li, Jiabao Sheng, Wushour Slamu
There are major challenges of low-resource agglutinative text classification the lack of labeled data in a target domain and morphologic diversity of derivations in language structures.
1 code implementation • 3 May 2022 • Zhendong Yang, Zhe Li, Mingqi Shao, Dachuan Shi, Zehuan Yuan, Chun Yuan
The current distillation algorithm usually improves students' performance by imitating the output of the teacher.
1 code implementation • 26 Mar 2022 • Jinyu Yang, Zhe Li, Song Yan, Feng Zheng, Aleš Leonardis, Joni-Kristian Kämäräinen, Ling Shao
Particularly, we are the first to provide depth quality evaluation and analysis of tracking results in depth-friendly scenarios in RGBD tracking.
no code implementations • 23 Feb 2022 • Canjie Luo, Yuanzhi Zhu, Lianwen Jin, Zhe Li, Dezhi Peng
Specifically, we propose a style bank to parameterize the specific handwriting styles as latent vectors, which are input to a generator as style priors to achieve the corresponding handwritten styles.
no code implementations • 22 Feb 2022 • Zhe Li, Andreas S. Tolias, Xaq Pitkow
Many complex systems are composed of interacting parts, and the underlying laws are usually simple and universal.
no code implementations • 16 Feb 2022 • Honglong Chen, Zhe Li, Zhu Wang, Zhichen Ni, Junjian Li, Ge Xu, Abdul Aziz, Feng Xia
As an effective way to alleviate information overload, recommender system can improve the quality of various services by adding application data generated by users on edge devices, such as visual and textual information, on the basis of sparse rating data.
no code implementations • 16 Feb 2022 • Zhu Wang, Honglong Chen, Zhe Li, Kai Lin, Nan Jiang, Feng Xia
Fortunately, context-aware recommender systems can alleviate the sparsity problem by making use of some auxiliary information, such as the information of both the users and items.
no code implementations • 16 Feb 2022 • Zhichen Ni, Honglong Chen, Zhe Li, Xiaomeng Wang, Na Yan, Weifeng Liu, Feng Xia
The vehicles can offload the computation intensive tasks to the cloud to save the resource of edge.
1 code implementation • 23 Nov 2021 • Zhendong Yang, Zhe Li, Xiaohu Jiang, Yuan Gong, Zehuan Yuan, Danpei Zhao, Chun Yuan
Global distillation rebuilds the relation between different pixels and transfers it from teachers to students, compensating for missing global information in focal distillation.
no code implementations • 1 Oct 2021 • Chengyi Tu, Paolo DOdorico, Zhe Li, Samir Suweis
The sustainable use of common-pool resources (CPRs) is a major environmental governance challenge because of their possible over-exploitation.
no code implementations • ICCV 2021 • Yuxiang Zhang, Zhe Li, Liang An, Mengcheng Li, Tao Yu, Yebin Liu
Overall, we propose the first light-weight total capture system and achieves fast, robust and accurate multi-person total motion capture performance.
1 code implementation • CVPR 2021 • Tianwei Wang, Yuanzhi Zhu, Lianwen Jin, Dezhi Peng, Zhe Li, Mengchao He, Yongpan Wang, Canjie Luo
Specifically, we integrate IFA into the two most prevailing text recognition streams (attention-based and CTC-based) and propose attention-guided dense prediction (ADP) and Extended CTC (ExCTC).
1 code implementation • 9 Jun 2021 • Sheng Fang, Kaiyu Li, Zhe Li
Aimed at both questions this paper proposes the salient positions-based attention scheme SPANet, which is inspired by some interesting observations on the attention maps and affinity matrices generated in self-attention scheme.
1 code implementation • 26 May 2021 • Chun-Ta Lu, Yun Zeng, Da-Cheng Juan, Yicheng Fan, Zhe Li, Jan Dlabal, Yi-Ting Chen, Arjun Gopalan, Allan Heydon, Chun-Sung Ferng, Reah Miyara, Ariel Fuxman, Futang Peng, Zhen Li, Tom Duerig, Andrew Tomkins
In this work, we propose CARLS, a novel framework for augmenting the capacity of existing deep learning frameworks by enabling multiple components -- model trainers, knowledge makers and knowledge banks -- to concertedly work together in an asynchronous fashion across hardware platforms.
1 code implementation • 27 Apr 2021 • Haotian Yan, Zhe Li, Weijian Li, Changhu Wang, Ming Wu, Chuang Zhang
It is also worth pointing that, given identical strong data augmentations, the performance improvement of ConTNet is more remarkable than that of ResNet.
1 code implementation • 20 Apr 2021 • Gido M. van de Ven, Zhe Li, Andreas S. Tolias
As a proof-of-principle, here we implement this strategy by training a variational autoencoder for each class to be learned and by using importance sampling to estimate the likelihoods p(x|y).
no code implementations • CVPR 2021 • Zhe Li, Tao Yu, Zerong Zheng, Kaiwen Guo, Yebin Liu
By contributing a novel reconstruction framework which contains pose-guided keyframe selection and robust implicit surface fusion, our method fully utilizes the advantages of both tracking-based methods and tracking-free inference methods, and finally enables the high-fidelity reconstruction of dynamic surface details even in the invisible regions.
1 code implementation • CVPR 2021 • Zhe Li, Yazan Abu Farha, Juergen Gall
To demonstrate the effectiveness of timestamp supervision, we propose an approach to train a segmentation model using only timestamps annotations.
Ranked #2 on
Weakly Supervised Action Localization
on GTEA
1 code implementation • 27 Oct 2020 • Kaiyu Li, Zhe Li, Sheng Fang
In this paper, we improve the semantic segmentation network UNet++ and propose a fully convolutional siamese network (Siam-NestedUNet) for change detection.
Change Detection
Change detection for remote sensing images
+1
no code implementations • 20 Jul 2020 • Zhe Li, Lianwen Jin, Songxuan Lai, Yecheng Zhu
Handwritten mathematical expression recognition (HMER) is an important research direction in handwriting recognition.
no code implementations • 18 May 2020 • Zechun Liu, Xiangyu Zhang, Zhiqiang Shen, Zhe Li, Yichen Wei, Kwang-Ting Cheng, Jian Sun
To tackle these three naturally different dimensions, we proposed a general framework by defining pruning as seeking the best pruning vector (i. e., the numerical value of layer-wise channel number, spacial size, depth) and construct a unique mapping from the pruning vector to the pruned network structures.
no code implementations • CVPR 2020 • Zhe Li, Tao Yu, Chuanyu Pan, Zerong Zheng, Yebin Liu
In this paper, we propose an efficient method for robust 3D self-portraits using a single RGBD camera.
no code implementations • 7 Mar 2020 • Zhe Li, Chunhua Sun, Chunli Liu, Xiayu Chen, Meng Wang, Yezheng Liu
To address these issues, we focus on semi-supervised outlier detection with few identified anomalies, in the hope of using limited labels to achieve high detection accuracy.
no code implementations • 2 Mar 2020 • Liang Jiang, Zujie Wen, Zhongping Liang, Yafang Wang, Gerard de Melo, Zhe Li, Liangzhuang Ma, Jiaxing Zhang, Xiaolong Li, Yuan Qi
The long-term teacher draws on snapshots from several epochs ago in order to provide steadfast guidance and to guarantee teacher--student differences, while the short-term one yields more up-to-date cues with the goal of enabling higher-quality updates.
no code implementations • NeurIPS 2019 • Zhe Li, Wieland Brendel, Edgar Y. Walker, Erick Cobos, Taliah Muhammad, Jacob Reimer, Matthias Bethge, Fabian H. Sinz, Xaq Pitkow, Andreas S. Tolias
We propose to regularize CNNs using large-scale neuroscience data to learn more robust neural features in terms of representational similarity.
no code implementations • ICCV 2019 • Yuyin Zhou, Zhe Li, Song Bai, Chong Wang, Xinlei Chen, Mei Han, Elliot Fishman, Alan Yuille
Accurate multi-organ abdominal CT segmentation is essential to many clinical applications such as computer-aided intervention.
Ranked #4 on
Medical Image Segmentation
on Synapse multi-organ CT
no code implementations • 28 Feb 2019 • Siyu Liao, Zhe Li, Liang Zhao, Qinru Qiu, Yanzhi Wang, Bo Yuan
Deep neural networks (DNNs), especially deep convolutional neural networks (CNNs), have emerged as the powerful technique in various machine learning applications.
no code implementations • 12 Dec 2018 • Zhe Li, Caiwen Ding, Siyue Wang, Wujie Wen, Youwei Zhuo, Chang Liu, Qinru Qiu, Wenyao Xu, Xue Lin, Xuehai Qian, Yanzhi Wang
It is a challenging task to have real-time, efficient, and accurate hardware RNN implementations because of the high sensitivity to imprecision accumulation and the requirement of special activation function implementations.
no code implementations • NeurIPS 2018 • Mingrui Liu, Zhe Li, Xiaoyu Wang, Jin-Feng Yi, Tianbao Yang
Negative curvature descent (NCD) method has been utilized to design deterministic or stochastic algorithms for non-convex optimization aiming at finding second-order stationary points or local minima.
2 code implementations • 28 Sep 2018 • Yezheng Liu, Zhe Li, Chong Zhou, Yuanchun Jiang, Jianshan Sun, Meng Wang, Xiangnan He
In this paper, we approach outlier detection as a binary-classification issue by sampling potential outliers from a uniform reference distribution.
no code implementations • 30 Aug 2018 • Yan Yan, Tianbao Yang, Zhe Li, Qihang Lin, Yi Yang
However, their theoretical analysis of convergence of the training objective and the generalization error for prediction is still under-explored.
no code implementations • CVPR 2019 • Jian Ren, Zhe Li, Jianchao Yang, Ning Xu, Tianbao Yang, David J. Foran
In this paper, we propose an Ecologically-Inspired GENetic (EIGEN) approach that uses the concept of succession, extinction, mimicry, and gene duplication to search neural network structure from scratch with poorly initialized simple network and few constraints forced during the evolution, as we assume no prior knowledge about the task domain.
no code implementations • 3 Jun 2018 • Zhe Li, Xuehan Xiong, Zhou Ren, Ning Zhang, Xiaoyu Wang, Tianbao Yang
In this paper, we study how to design a genetic programming approach for optimizing the structure of a CNN for a given task under limited computational resources yet without imposing strong restrictions on the search space.
no code implementations • 10 May 2018 • Zhe Li, Ji Li, Ao Ren, Caiwen Ding, Jeffrey Draper, Qinru Qiu, Bo Yuan, Yanzhi Wang
Recently, Deep Convolutional Neural Network (DCNN) has achieved tremendous success in many machine learning applications.
no code implementations • 11 Apr 2018 • Ziyi Zhao, Krittaphat Pugdeethosapol, Sheng Lin, Zhe Li, Caiwen Ding, Yanzhi Wang, Qinru Qiu
The topic modeling discovers the latent topic probability of the given text documents.
no code implementations • 20 Mar 2018 • Zhe Li, Xiaolong Ma, Hongjia Li, Qiyuan An, Aditya Singh Rathore, Qinru Qiu, Wenyao Xu, Yanzhi Wang
It is of vital importance to enable 3D printers to identify the objects to be printed, so that the manufacturing procedure of an illegal weapon can be terminated at the early stage.
no code implementations • 20 Mar 2018 • Zhe Li, Shuo Wang, Caiwen Ding, Qinru Qiu, Yanzhi Wang, Yun Liang
Recurrent Neural Networks (RNNs) are becoming increasingly important for time series-related applications which require efficient and real-time implementations.
no code implementations • 14 Mar 2018 • Shuo Wang, Zhe Li, Caiwen Ding, Bo Yuan, Yanzhi Wang, Qinru Qiu, Yun Liang
The previous work proposes to use a pruning based compression technique to reduce the model size and thus speedups the inference on FPGAs.
no code implementations • 25 Feb 2018 • Kun Hu, Zhe Li, Ying Liu, Luyin Cheng, Qi Yang, Yan Li
In the first prediction part, we focus on predicting the downward trend, which is an earlier stage of the customer lifecycle compared to churn.
no code implementations • 18 Feb 2018 • Yanzhi Wang, Caiwen Ding, Zhe Li, Geng Yuan, Siyu Liao, Xiaolong Ma, Bo Yuan, Xuehai Qian, Jian Tang, Qinru Qiu, Xue Lin
Hardware accelerations of deep learning systems have been extensively investigated in industry and academia.
no code implementations • 15 Feb 2018 • Hongjia Li, Xiaolong Ma, Aditya Singh Rathore, Zhe Li, Qiyuan An, Chen Song, Wenyao Xu, Yanzhi Wang
The rapid development in additive manufacturing (AM), also known as 3D printing, has brought about potential risk and security issues along with significant benefits.
no code implementations • 3 Feb 2018 • Xiaolong Ma, Yi-Peng Zhang, Geng Yuan, Ao Ren, Zhe Li, Jie Han, Jingtong Hu, Yanzhi Wang
However, in these works, the memory design optimization is neglected for weight storage, which will inevitably result in large hardware cost.
11 code implementations • 22 Nov 2017 • Fangzhou Liao, Ming Liang, Zhe Li, Xiaolin Hu, Sen Song
The model consists of two modules.
1 code implementation • CVPR 2018 • Zhe Li, Chong Wang, Mei Han, Yuan Xue, Wei Wei, Li-Jia Li, Li Fei-Fei
Accurate identification and localization of abnormalities from radiology images play an integral part in clinical diagnosis and treatment planning.
no code implementations • 9 Sep 2017 • Tianbao Yang, Zhe Li, Lijun Zhang
In this paper, we present a simple analysis of {\bf fast rates} with {\it high probability} of {\bf empirical minimization} for {\it stochastic composite optimization} over a finite-dimensional bounded convex set with exponential concave loss functions and an arbitrary convex regularization.
no code implementations • 29 Aug 2017 • Caiwen Ding, Siyu Liao, Yanzhi Wang, Zhe Li, Ning Liu, Youwei Zhuo, Chao Wang, Xuehai Qian, Yu Bai, Geng Yuan, Xiaolong Ma, Yi-Peng Zhang, Jian Tang, Qinru Qiu, Xue Lin, Bo Yuan
As the size of DNNs continues to grow, it is critical to improve the energy efficiency and performance while maintaining accuracy.
no code implementations • 13 Jun 2017 • Zhe Li, Xiaoyu Wang, Xutao Lv, Tianbao Yang
By doing this, we show that previous deep CNNs such as GoogLeNet and Inception-type Nets can be compressed dramatically with marginal drop in performance.
no code implementations • 13 Mar 2017 • Ning Liu, Zhe Li, Zhiyuan Xu, Jielong Xu, Sheng Lin, Qinru Qiu, Jian Tang, Yanzhi Wang
Automatic decision-making approaches, such as reinforcement learning (RL), have been applied to (partially) solve the resource allocation problem adaptively in the cloud computing system.
no code implementations • 12 Mar 2017 • Ji Li, Zihao Yuan, Zhe Li, Caiwen Ding, Ao Ren, Qinru Qiu, Jeffrey Draper, Yanzhi Wang
Recently, Deep Convolutional Neural Networks (DCNNs) have made unprecedented progress, achieving the accuracy close to, or even better than human-level perception in various tasks.
no code implementations • ICML 2017 • Liang Zhao, Siyu Liao, Yanzhi Wang, Zhe Li, Jian Tang, Victor Pan, Bo Yuan
Recently low displacement rank (LDR) matrices, or so-called structured matrices, have been proposed to compress large-scale neural networks.
no code implementations • 18 Nov 2016 • Ao Ren, Ji Li, Zhe Li, Caiwen Ding, Xuehai Qian, Qinru Qiu, Bo Yuan, Yanzhi Wang
Stochastic Computing (SC), which uses bit-stream to represent a number within [-1, 1] by counting the number of ones in the bit-stream, has a high potential for implementing DCNNs with high scalability and ultra-low hardware footprint.
no code implementations • 12 Apr 2016 • Tianbao Yang, Qihang Lin, Zhe Li
This paper fills the gap between practice and theory by developing a basic convergence analysis of two stochastic momentum methods, namely stochastic heavy-ball method and the stochastic variant of Nesterov's accelerated gradient method.
no code implementations • NeurIPS 2016 • Zhe Li, Boqing Gong, Tianbao Yang
To exhibit the optimal dropout probabilities, we analyze the shallow learning with multinomial dropout and establish the risk bound for stochastic optimization.